Hi all,

I am new to STATA. I have difficulty in doing M&A analysis when I try to merge M&A data from Thomson-Reuters with data from the 13f dataset. I want to add announcement dates from Thomson-Reuters to the 13f dataset to calculate institutional ownership concentration. But there are many same acusip6 (6-dig cusips of acquirors) with different announcement dates in dataset 1, and different mgrno (i.e. manager numbers) with various rdate (i.e. report date) in dataset 2. I want to get a merged dataset that each announcement date is matched with all mgrno that have the same acusip6. Both datasets have the same but duplicate acusip6. Could anyone tell me how to do that?

Part of these two datasets are as follows:
Dataset1
ann_date deal_value acusip6
14-Dec-09 118.09 002824
10-Sep-09 410 002824
28-Sep-09 7603.45 002824
12-Jan-09 1377.735 002824
14-Oct-09 6.819 004848
05-Jun-09 207.52 00508Y
Dataset2
mgrno acusip6 rdate shrheld shrout
185 002824 30-Jun-09 1585993 1545459
185 002824 31-Mar-09 1606049 1545383
185 002824 30-Sep-09 1540941 1545912
185 002824 31-Dec-09 1543268 1546738
195 002824 31-Dec-09 328758 1546738
195 002824 30-Jun-09 518482 1545459
195 002824 30-Sep-09 2300159 1545912
195 002824 31-Mar-09 497639 1545383
205 002824 30-Jun-09 66602 1545459
205 002824 31-Mar-09 67229 1545383
205 002824 31-Dec-09 68792 1546738
205 002824 30-Sep-09 66977 1545912
220 002824 31-Mar-09 688465 1545383
220 002824 30-Jun-09 146925 1545459
220 002824 30-Sep-09 287175 1545912
220 002824 31-Dec-09 988025 1546738
260 002824 30-Jun-09 320000 1545459
260 002824 31-Dec-09 320000 1546738
260 002824 31-Mar-09 320000 1545383
260 002824 30-Sep-09 320000 1545912
350 002824 30-Jun-09 17139 1545459
350 002824 31-Mar-09 25384 1545383
350 002824 30-Sep-09 13627 1545912
350 002824 31-Dec-09 13827 1546738
482 002824 30-Sep-09 165905 1545912
482 002824 31-Dec-09 233310 1546738
482 002824 30-Jun-09 235878 1545459
482 002824 31-Mar-09 275037 1545383
650 002824 31-Mar-09 2677987 1545383
650 002824 30-Sep-09 364531 1545912
650 002824 30-Jun-09 693589 1545459
650 002824 31-Dec-09 338134 1546738
800 002824 30-Jun-09 125163 1545459
800 002824 31-Mar-09 123773 1545383
885 002824 31-Mar-09 2616963 1545383
885 002824 30-Jun-09 2868436 1545459
885 002824 31-Dec-09 1764664 1546738
885 002824 30-Sep-09 1834466 1545912
1275 002824 30-Sep-09 37474 1545912
1275 002824 31-Mar-09 45308 1545383
1275 002824 31-Dec-09 36761 1546738
1275 002824 30-Jun-09 37389 1545459
1285 002824 30-Sep-09 281509 1545912
1285 002824 30-Jun-09 284016 1545459
1285 002824 31-Dec-08 278202 1545383
1285 002824 31-Dec-09 278049 1546738
180 004848 30-Sep-09 843620 11179
180 004848 30-Jun-09 868720 11282
180 004848 31-Dec-09 679860 11647
180 004848 31-Mar-09 868720 11468
5300 004848 30-Jun-09 39500 11282
5300 004848 30-Sep-09 39500 11179
5300 004848 31-Mar-09 39500 11468
5300 004848 31-Dec-09 39500 11647
5720 004848 31-Mar-09 1000 11468
5720 004848 30-Jun-09 1000 11282
7815 004848 31-Dec-09 13400 11647
7900 004848 30-Jun-09 23525 11282
7900 004848 30-Sep-09 21209 11647
7900 004848 30-Sep-09 21209 11179
220 00508Y 31-Mar-09 200 41201
650 00508Y 31-Dec-09 21600 43267
650 00508Y 30-Sep-09 22100 43086
650 00508Y 31-Mar-09 25000 41201
650 00508Y 30-Jun-09 21600 40913
1365 00508Y 31-Dec-09 9620 43267
2470 00508Y 30-Jun-09 60698 40913
2470 00508Y 31-Dec-09 64567 43267
2470 00508Y 30-Sep-09 77429 43086
2470 00508Y 31-Mar-09 39089 41201
4714 00508Y 31-Dec-09 16300 43267
4719 00508Y 30-Jun-09 5218799 40913
4719 00508Y 31-Dec-09 5452799 43267
4719 00508Y 30-Sep-09 5443499 43086
4719 00508Y 31-Mar-09 4108799 41201
5720 00508Y 30-Jun-09 4877 40913
5720 00508Y 30-Sep-09 4677 43086
5720 00508Y 31-Mar-09 8477 41201
5720 00508Y 31-Dec-09 4977 43267
6093 00508Y 31-Dec-09 6321 43267
6093 00508Y 30-Jun-09 20166 40913
6093 00508Y 30-Sep-09 23503 43086
6098 00508Y 30-Sep-09 1421604 43086
6098 00508Y 30-Jun-09 423796 40913
6132 00508Y 30-Jun-09 258934 40913
6132 00508Y 30-Sep-09 119223 43086
6132 00508Y 31-Dec-09 47328 43267
6132 00508Y 31-Mar-09 245400 41201
6155 00508Y 31-Mar-09 12386 41201
Thanks a lot,
Wenyu